Davos 2026: Are we in an AI bubble? Andrew Ng says it depends on where you look

AI pioneer Andrew Ng with Moneycontrol's Chandra R Srikanth at the World Economic Forum in Davos on January 19

• Andrew Ng says AI application layer is underinvested, not a bubble
• Ng warns of overinvestment risk in AI model training due to high costs
• Demand for AI inference infrastructure is rapidly increasing

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Is there an AI bubble? The question currently looms over the entire technology landscape.

Andrew Ng, one of the leading voices in artificial intelligence, told Moneycontrol in an interview that while he does not see a bubble in some parts of the market, there are other parts where it is reasonable to ask the question.

In fact, he believes that the application layer feels "underinvested". "If I look at the actual business use cases, applications and the application layer, other than the AI foundation model layer, I don't think there's a bubble," Ng, the founder of DeepLearning.AI, managing general partner at AI Fund and co-founder of Coursera, told Moneycontrol on January 19 at the World Economic Forum (WEF) 2026 in Davos.

Also read: Davos 2026: Andrew Ng backs open source as key pillar of India’s AI strategy

Ng agreed that hype has risen rapidly but noted that actual business value is also increasing quickly. "It's rising very rapidly from a low base in terms of the number of business applications that large companies are able to build and deploy. We're seeing this playbook in Silicon Valley. Maybe it's a small percentage now, but it's compounding very rapidly," he said.

Ng added that more capacity will be needed, as the demand for AI inference is "through the roof", be it by way of open weight models, open source models or the proprietary models.

"I wish we could use more of these, but for various reasons, be it cost capacity, many teams are being throttled in how much they can use. So I'm excited about the infrastructure build-out for AI inference infra," he said.

Also read: Davos 2026: Andrew Ng says AI-driven job losses have been overstated

Ng however, cautioned that this does not mean no one will lose money. "It is possible to still have an oversupply, but I think a lot of that capacity will get used," he said.

The area where the risk of overinvestment is highest is AI model training. Ng said. This is because the cost of training AI models has risen so much that if any of the companies footing the large bills run into trouble and begin to pull back, some of the investments could face a more uncertain future, he said.

"I am still cautiously optimistic and generally bullish about the sector and most of the leading players in the field," Ng said.